Running Speed In School-age Children And Prevalence Of Diabetes Mellitus In Adulthood

BACKGROUND: Previous studies have reported that the running speed of school-age children is influenced mainly by genetic factors. Children who are fast at short distances may possess dominant fast muscle fibers, while those who are fast at long distances possess dominant slow fibers. Fast muscle fibers are characterized as insulin-insensitive, while slow fibers are insulin sensitive. Therefore, a different relationship may potentially exist between running speed at short vs. long distances in school-age children and the prevalence of type 2 diabetes in adulthood. PURPOSE: This study investigated the relationship between running speed in school-aged children and the prevalence of diabetes mellitus in adulthood. METHODS: 3,105 adults (aged 20 − 80 years) participated in a cross-sectional internet survey. In addition to the demographic and physical characteristics, we asked about relative running speeds (slow, somewhat slow, average, somewhat fast, fast) for short and long running distances during childhood. We also asked about the presence of diabetes at the time of the study in adulthood. Logistic regression models were used to evaluate the relationship between running speed during childhood and diabetes during adulthood, and multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) after adjusting for sex, age, BMI, physical activity, smoking habit, and drinking habit. RESULTS: The number of participants with self-reported diabetes was 228. For short-distance running speeds, using the "slow" group as reference, the multivariable-adjusted ORs (95% CIs) of diabetes were 0.89 (0.56 − 1.40) for "somewhat slow", 0.73 (0.47 − 1.13) for "average", 0.62 (0.39 − 1.00) for "somewhat fast", and 0.51 (0.30 − 0.88) for "fast" group (P for trend = 0.004). For long-distance running speeds, using the "slow" group as reference, the multivariable-adjusted ORs (95% CIs) of diabetes were 0.67 (0.44 − 1.04), 0.62 (0.42 − 0.92), 0.54 (0.33 − 0.86), and 0.27 (0.12 − 0.59) in the corresponding groups (P for trend <0.001). CONCLUSIONS: Faster short-distance running speed in school-aged children was associated with a lower prevalence of diabetes in adulthood. In addition, we observed a similar, yet slightly stronger, association for long-distance running speed. However, prospective studies are needed.

Authors

Institutions

Publication Details

Journal
Medicine & Science in Sports & Exercise
Published
2024-09-16
DOI
https://doi.org/10.1249/01.mss.0001058588.22112.bd
Primary Topic
Cardiovascular and exercise physiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Running Speed In School-age Children And Prevalence Of Diabetes Mellitus In Adulthood

Xuemei Sui, Takayuki Akimoto, I‐Min Lee, Sakura Koriyama et al.
Medicine & Science in Sports & Exercise
Cardiovascular and exercise physiology
article

Running Speed In School-age Children And Prevalence Of Diabetes Mellitus In Adulthood

Xuemei Sui, Takayuki Akimoto, I‐Min Lee, Sakura Koriyama, Robert A. Sloan, M Kinoshita, Xiangyu Zhai, Susumu S. Sawada, Yuko Nagasaka, Duck-chul Lee
article en

Abstract

BACKGROUND: Previous studies have reported that the running speed of school-age children is influenced mainly by genetic factors. Children who are fast at short distances may possess dominant fast muscle fibers, while those who are fast at long distances possess dominant slow fibers. Fast muscle fibers are characterized as insulin-insensitive, while slow fibers are insulin sensitive. Therefore, a different relationship may potentially exist between running speed at short vs. long distances in school-age children and the prevalence of type 2 diabetes in adulthood. PURPOSE: This study investigated the relationship between running speed in school-aged children and the prevalence of diabetes mellitus in adulthood. METHODS: 3,105 adults (aged 20 − 80 years) participated in a cross-sectional internet survey. In addition to the demographic and physical characteristics, we asked about relative running speeds (slow, somewhat slow, average, somewhat fast, fast) for short and long running distances during childhood. We also asked about the presence of diabetes at the time of the study in adulthood. Logistic regression models were used to evaluate the relationship between running speed during childhood and diabetes during adulthood, and multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) after adjusting for sex, age, BMI, physical activity, smoking habit, and drinking habit. RESULTS: The number of participants with self-reported diabetes was 228. For short-distance running speeds, using the "slow" group as reference, the multivariable-adjusted ORs (95% CIs) of diabetes were 0.89 (0.56 − 1.40) for "somewhat slow", 0.73 (0.47 − 1.13) for "average", 0.62 (0.39 − 1.00) for "somewhat fast", and 0.51 (0.30 − 0.88) for "fast" group (P for trend = 0.004). For long-distance running speeds, using the "slow" group as reference, the multivariable-adjusted ORs (95% CIs) of diabetes were 0.67 (0.44 − 1.04), 0.62 (0.42 − 0.92), 0.54 (0.33 − 0.86), and 0.27 (0.12 − 0.59) in the corresponding groups (P for trend <0.001). CONCLUSIONS: Faster short-distance running speed in school-aged children was associated with a lower prevalence of diabetes in adulthood. In addition, we observed a similar, yet slightly stronger, association for long-distance running speed. However, prospective studies are needed.

Medicine & Science in Sports & ExerciseVol. 56(10S)
Kagoshima University (JP), Waseda University (JP), Iowa State University (US), Harvard University Press (US)
Openalex Percentile: Top 70%
Cardiovascular and exercise physiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.